Estimation of Extreme Regional Precipitation under Climate Change

Abstract

A methodology for estimating extreme regional precipitation using atmospheric circulation patterns is developed. A sequence of observed daily air pressure distributions is used to define circulation patterns. The classification of the circulation patterns is constructed using a fuzzy rule based approach. A multivariate stochastic model describes the link between circulation patterns and daily precipitation amounts at a number of selected locations. Model parameters are estimated using observed data. The model is extended in order to describe precipitation amounts at ungauged locations, so that a real precipitation can also be analyzed. To assess extreme daily precipitation under changed climate conditions, circulation patterns derived from GCM output pressure values are used as conditioning parameters in the stochastic precipitation model. A long-term simulation is then used to estimate extreme daily aerial precipitation. The possibility to obtain extremes not only for daily but also for shorter time steps (1–12 hours) is discussed. The methodology is illustrated by results obtained for subcatchments of the Ruhr basin (Germany).